We examine, both theoretically and empirically, top-management compensation in the presence of agency conflicts when shareholders have delegated governance responsibilities to a self-interested Boa...
This paper proposes a new analytical framework to quantify and correct for scale compatibility bias in the assessment of trade-off weights in multiattribute value analysis. The procedure is demonstrated with an application to a fisheries management problem. Trade-off judgments are elicited from a group of fisheries experts with management responsibility in the Lake Erie basin. Then we use a Bayesian method to compute posterior probability distributions of attribute weights. In computing the Bayesian weights, our measurement model assumes that the weight ratios produced by each respondent's judgments are subject to random error and an unknown scale compatibility bias. Ratios are log-transformed and analyzed by a Bayesian linear model with a noninformative prior distribution. Posterior distributions are then developed for the weights and the bias. We estimate the compatibility bias for each person and, in most cases, it is found to be large and in the predicted direction, suggesting the importance of its consideration in deriving trade-off weights. In addition, the Bayesian framework is shown to be useful for quantifying the value of additional information about multiattribute weights. Finally, a simple heuristic procedure for assessing the weights appears to be effective in eliminating the bias.
We take a structural approach to assessing innovation. We develop a comprehensive set of measures to assess an innovation's locus, type, and characteristics. We find that the concepts of competence...
Previous research has examined whether price dispersion exists in theoretically highly efficient Internet markets. However, much of the previous work has been focused on industries with low cost an...
Systems composed of activity choices that interact in nonsimple ways can allow firms to create and sustain a competitive advantage. However, in complex systems, decision makers may not always have a precise understanding of the exact strength of the interaction between activities. Likewise, incentive and accounting systems may lead decision makers to ignore or misperceive interactions. This paper studies formally the consequences of misperceiving interaction effects between activity choices. Our results suggest that misperceptions with respect to complements are more costly than with respect to substitutes. As a result, firms should optimally invest more to gather information about interactions among complementary activities—e.g., concerning network effects—than about interactions among substitute activities. Similarly, the use of division-based incentive schemes appears to be more advisable for divisions whose products are substitutes than for divisions that produce complements. It is further shown that system fragility is not necessarily positively correlated with the strength ofthe interaction between choices. While systems of complements become increasingly fragile as the strength of interaction increases, systems of substitutes can become increasingly stable.
In this paper, we explore the locus of profitable pollution reduction. We propose that managers underestimate the full value of some means of pollution reduction and so under exploit these means. Based on evidence from previous studies, we argue that waste prevention often provides unexpected innovation offsets, and that onsite waste treatment often provides unexpected cost. We use statistical methods to test the direction and significance of the relationship between the various means of pollution reduction and profitability. We find strong evidence that waste prevention leads to financial gain, but we find no evidence that firms profit from reducing pollution by other means. Indeed, we find evidence that the bene fits of waste prevention alone are responsible for the observed association between lower emissions and profitability.
Some firms make all their products to order while others make them to stock. There are a number of firms that maintain a middle ground, where some items are made to stock and others are made to order. This paper was motivated by a consumer product company faced with the decision about which items to make to stock and which ones to make to order, and the inventory and production policy for the make-to-stock items. The production environment is characterized by multiple items, setup times between the production of consecutive items, limited capacity, and congestion effects. In such an environment, making an item to order reduces inventory costs for that item, but might increase the lot size and inventory costs for the items made to stock. Also, lead times increase because of congestion effects, resulting in higher safety stocks for make-to-stock items and lower service levels for make-to-order items, thus leading to a complex trade-off. We develop a nonlinear, integer programming formulation of the problem. We present an efficient heuristic to solve the problem, which was motivated by key results for a special case of the problem without congestion effects that can be solved optimally. We also develop a lower bound to evaluate the performance of the heuristic. A computational study indicates that the heuristic performs well. We discuss the application of the model in a large firm and the resulting insights. We also provide insights into the impact of various problem parameters on the make-to-order versus make-to-stock decisions using a computational study. In particular, we find that the average number of setups of an item selected for make-to-stock production is always less than half the average number of setups of the item if it were to be made to order. Also, factors other than an item's demand, such as its setup time, processing time, and unit holding cost, impact the make-to-order versus make-to-stock decision.
We study simultaneous investment and financing decisions made by incumbent owners in the presence of capital market imperfections. We present a theory for how the optimal combination of debt and equity financing depends on the firm's internal funds. We identify complementarities between the two financial instruments. We test these predictions empirically with panel data on 3,119 corporations in the COMPUSTAT database. Our estimates using instrumental variable techniques support our theoretical predictions regarding the link between internal funds and capital investments, as well as the interaction effects between debt and new equity. We explore implications for managers, financiers, and policy makers.
Pricing European-style Asian options based on the arithmetic average, under the Black and Scholes model, involves estimating an integral (a mathematical expectation) for which no easily computable analytical solution is available. Pricing their American-style counterparts, which provide early exercise opportunities, poses the additional difficulty of solving a dynamic optimization problem to determine the optimal exercise strategy. A procedure for pricing American-style Asian options of the Bermudan flavor, based on dynamic programming combined with finite-element piecewise-polynomial approximation of the value function, is developed here. A convergence proof is provided. Numerical experiments illustrate the consistency and efficiency of the PROCEDURE. Theoretical properties of the value function and of the optimal exercise strategy are also established.